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RichardErkhov/
thrunlab_-_sparse_mistral_7b_refined_web_50p_2024-04-13-4bits

Name: thrunlab_-_sparse_mistral_7b_refined_web_50p_2024-04-13-4bits
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sparse_mistral_7b_refined_web_50p_2024-04-13 - bnb 4bits

Model creator: https://huggingface.co/thrunlab/
Original model: https://huggingface.co/thrunlab/sparse_mistral_7b_refined_web_50p_2024-04-13/

Original model description:

license: apache-2.0 base_model: mistralai/Mistral-7B-v0.1 tags:

generated_from_trainer model-index:
name: sparse_mistral_7b_refined_web_50p_2024-04-13 results: []

sparse_mistral_7b_refined_web_50p_2024-04-13

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.1985

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 1
eval_batch_size: 4
seed: 0
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 8
total_train_batch_size: 32
total_eval_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 2350

Training results

Training Loss	Epoch	Step	Validation Loss
2.3391	0.01	25	2.4196
2.2711	0.02	50	2.3577
2.3054	0.02	75	2.3158
2.2795	0.03	100	2.2966
2.3175	0.04	125	2.2846
2.2388	0.05	150	2.2766
2.1679	0.06	175	2.2705
2.2996	0.06	200	2.2678
2.2788	0.07	225	2.2647
2.2448	0.08	250	2.2637
2.1837	0.09	275	2.2624
2.2089	0.1	300	2.2621
2.2686	0.1	325	2.2601
2.2254	0.11	350	2.2593
2.162	0.12	375	2.2590
2.2687	0.13	400	2.2563
2.2595	0.14	425	2.2571
2.186	0.14	450	2.2564
2.2689	0.15	475	2.2580
2.2472	0.16	500	2.2554
2.2005	0.17	525	2.2553
2.1983	0.18	550	2.2552
2.2388	0.18	575	2.2547
2.1443	0.19	600	2.2555
2.2198	0.2	625	2.2534
2.3008	0.21	650	2.2536
2.179	0.22	675	2.2521
2.2069	0.22	700	2.2531
2.1819	0.23	725	2.2526
2.1218	0.24	750	2.2536
2.1845	0.25	775	2.2515
2.2167	0.26	800	2.2510
2.2252	0.26	825	2.2520
2.1664	0.27	850	2.2519
2.1853	0.28	875	2.2530
2.1499	0.29	900	2.2513
2.2763	0.3	925	2.2517
2.2528	0.3	950	2.2518
2.2505	0.31	975	2.2500
2.1683	0.32	1000	2.2502
2.2177	0.33	1025	2.2501
2.238	0.34	1050	2.2516
2.193	0.34	1075	2.2507
2.2025	0.35	1100	2.2502
2.0944	0.36	1125	2.2512
2.2272	0.37	1150	2.2508
2.2264	0.38	1175	2.2500
2.1837	0.38	1200	2.2507
2.1444	0.39	1225	2.2489
2.2464	0.4	1250	2.2499
2.1388	0.41	1275	2.2508
2.193	0.42	1300	2.2492
2.2376	0.42	1325	2.2506
2.2212	0.43	1350	2.2478
2.2002	0.44	1375	2.2488
2.2729	0.45	1400	2.2484
2.2329	0.46	1425	2.2473
2.1919	0.46	1450	2.2481
2.2102	0.47	1475	2.2475
2.1466	0.48	1500	2.2473
2.1819	0.49	1525	2.2478
2.2558	0.5	1550	2.2468
2.2137	0.5	1575	2.2463
2.2288	0.51	1600	2.2466
2.1479	0.52	1625	2.2468
2.1726	0.53	1650	2.2471
2.1805	0.54	1675	2.2454
2.1505	0.54	1700	2.2470
2.1337	0.55	1725	2.2465
2.2413	0.56	1750	2.2460
2.152	0.57	1775	2.2478
2.2669	0.58	1800	2.2471
2.2925	0.58	1825	2.2465
2.222	0.59	1850	2.2457
2.1308	0.6	1875	2.2466
2.201	0.61	1900	2.2456
2.2247	0.62	1925	2.2460
2.2426	0.62	1950	2.2463
2.2312	0.63	1975	2.2465
2.2679	0.64	2000	2.2464
2.1928	0.65	2025	2.2463
2.2087	0.66	2050	2.2455
2.1792	0.66	2075	2.2470
2.252	0.67	2100	2.2468
2.2018	0.68	2125	2.2456
2.2006	0.69	2150	2.2451
2.2076	0.7	2175	2.2449
2.2436	0.7	2200	2.2460
2.2156	0.71	2225	2.2477
2.1348	0.72	2250	2.2455
2.1338	0.73	2275	2.2450
2.2147	0.74	2300	2.2455
2.2766	0.74	2325	2.2444
2.204	0.75	2350	2.2458

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.15.0
Tokenizers 0.15.0

RichardErkhov/thrunlab_-_sparse_mistral_7b_refined_web_50p_2024-04-13-4bits

Original model description:

sparse_mistral_7b_refined_web_50p_2024-04-13

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
thrunlab_-_sparse_mistral_7b_refined_web_50p_2024-04-13-4bits